Productive Consumption Changing Market Dynamics: A Study in Brazilian DIY Cosmetics

Although several studies have discussed from various perspectives the market-change dynamics of consumption and how consumers impact them, only a few have looked at consumers who act as producers themselves and how they affect the market with their self-production practices. Using data from netnography, participant observation, introspection, and in-depth interviews, this study aims to understand the strategies used by the consumers of DIY (do-it-yourself) cosmetics, which affect the market dynamics and foster a specific market apart from mainstream. We identified three approaches: the strategies such consumers use to make their products; the sharing of consumption experiences; and the disclosure of these products and practices, thereby legitimating them.     

Structural decomposition analysis and input-output subsystems: Changes in CO2 emissions of Spanish service sectors (2000-2005)

The analysis of gas emissions by an input-output subsystem approach provides detailed insight into pollution generation in an economy. Structural decomposition analysis, on the other hand, identifies the factors behind the changes in key variables over time. Extending the input-output subsystem model to account for the changes in these variables reveals the channels by which environmental burdens are caused and transmitted throughout the production system. In this paper we propose a decomposition of the changes in the components of CO₂ emissions captured by an input-output subsystems representation. The empirical application is for the Spanish service sector, and the economic and environmental data are for years 2000 and 2005. Our results show that services increased their CO₂ emissions mainly because of a rise in the emissions generated by non-services to cover the final demand for services. The decomposed effects show a decrease in CO₂ emissions due to technological changes between 2000 and 2005 compensated by an increase in emissions caused by the rise in final demand of services. Finally, large asymmetries exist not only in the quantitative changes in the CO₂ emissions of the various services but also in the decomposed effects of these changes.     

Socioeconomic Index for Income and Poverty Prediction: A Sufficient Dimension Reduction Approach

The present paper introduces a novel method for the construction of Socioeconomic Status (SES) indices that are specific to a target variable of interest. It is based on the Sufficient Dimension Reduction (SDR) paradigm and uses a factorized model-based approach to simultaneously deal with predictor variables of mixed nature (i.e. quantitative, binary, and ordinal), which are usual in microeconomic data. These SES indices also identify relevant predictor variables using a two-step regularized matrix factorization approach. Using data from household surveys for Argentina (Encuesta Permanente de Hogares-EPH), the proposed method is compared with other existing dimension reduction algorithms such as standard Principal Component Analysis (PCA) and its version for mixed variables, regression on the full set of variables and Least Absolute Shrinkage and Selection Operator regression (LASSO).